Spread of Acceptance of Gays and Lesbians


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Using graph theory to spread the acceptance of gays and lesbians in society.

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Spread of Acceptance of Gays and Lesbians

  1. 1. Spread of Acceptance of Gay and Lesbian Relationships<br />Angela* and Dorea Vierling-Claassen<br />Lesley University <br />Community of Scholars Day<br />March 30, 2011<br />
  2. 2. Acceptance of Homosexuality<br />According to Gallup polls, the percentage of Americans who believe it is “morally acceptable” to be gay or lesbian has risen from 40% to 52% over the last 10 years.<br />What is driving the increasing acceptance levels?<br />One factor is relationships – a relationship with a gay or lesbian person interacts with a person’s prior beliefs and attitudes and is a powerful force to change one mind a time.<br />How can math help us understand this?<br />We can use math to model human interactions and social networks.<br />
  3. 3. Complex Networks<br />In recent years, there has been an explosion of interest in complex networks, which can model<br />Social networks, such as friendships or collaborative networks<br />Food webs, neural networks, and other biological networks<br />The internet, power grids, subway systems, and other constructed networks<br />Complex networks have an irregular structure.<br />Evolve dynamically in time<br />General trend is to move from considering small networks to networks with thousands or millions of nodes.<br />
  4. 4. Networks: the Math<br />Mathematically, networks are graphs, which are made up of nodes and edges<br />Once we have a graph, we can talk about characteristics of nodes and of the graph as a whol<br />
  5. 5. Characteristics<br />Degree of a node, which means a nodes total number of neighbors (other nodes connected to it by an edge)<br />Clustering coefficient – how likely are two neighbors of any node to be neighbors of each other (do my friends know each other?)<br />
  6. 6. Nodes can have attributes<br />
  7. 7. Edges can have attributes<br />
  8. 8. Modeling Acceptance <br />We start by assigning each node a random level of acceptance between 0 and 1, with higher numbers being more accepting.<br />We reserve an acceptance level of 1 to indicate that a node is gay or lesbian.<br />Over time, we allow interactions between the nodes to change the acceptance level of the nodes. However, gay and lesbian nodes always have an acceptance level of 1.<br />Edges between nodes are classified as “friend” or “family”<br />
  9. 9. How Minds are Changed<br />Randomly select a node N and friend or family member F.<br />If the acceptance levels of N and F are close enough to each other, both N and F move closer to their average level.<br />If the acceptance level is too far apart, the relationship is severed, the edge is removed, and N is randomly assigned a new friend by creating a new edge.<br />
  10. 10. Some Notes<br />Family ties are harder to break that friend ties (they will tolerate a larger degree of difference)<br />
  11. 11. What Happens Over Time (3000 steps)<br />Start<br />End<br />
  12. 12. Evolution of Queer vs. Straight Ties<br />Connections between gay nodes<br />Connections between similar collection of straight nodes.<br />
  13. 13. Impact of Non-Acceptance<br />When the average network acceptance level is low, gays and lesbians cluster into communities that are somewhat separate from straight communities<br />
  14. 14. Impact of Non-Acceptance<br />Such networks end up having two separate clusters – queers and straights<br />Queers are highly connected with other queers<br />Queers have fewer total connections (because many straight people have broken ties)<br />
  15. 15. Impact of Weak Ties<br />If all ties are easy to break, network becomes more unaccepting over time<br />
  16. 16. Impact of Strong Ties<br />Having strong ties (such as family ties) that resist breaking leads to a more accepting network over time.<br />This is true even if network is unaccepting to begin with.<br />
  17. 17. Networks which Include Acceptance<br />Here, all ties are relatively easy to break. The same phenomena occurs when we include family ties (harder to break).<br />
  18. 18. Impact of Family Ties<br />Increasing the number of ties that are difficult to break will pull the network toward more acceptance.<br />However, if a network starts out unaccepting, then even when it eventually becomes more accepting the clustering of gay people persists in this model.<br />
  19. 19. Preliminary Conclusions<br />Ties that are difficult to break change the overall acceptance level, so keep those ties!<br />Counteracting the clumping effects and social isolation of queers – interested in working on discovery of ways to do this through the model (without forcing an accepting network to start). If you have ideas, I’m all ears.<br />Some models lead toward everyone eventually being accepting – some end up with several clusters of opinions ranging from positive to negative.<br />
  20. 20. Next Steps<br />Modeling is currently implemented on a random network. One next step is to implement the model with a network that better models a social network, such as a “small world” type graph.<br />Connect with research on real social networks that include gays and lesbians – there is not much of this currently in existence.<br />Work on modeling what happens to an existing network with a mix of opinions when a person comes out. Can include in this mix both the impact of coming out and the likelihood of a person coming out based on opinions of connections.<br />